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S. S. R. GEEDIPALLI and A. K. Datta. Dept. of Biological & Environmental Engineering, Cornell Univ., 175 Riley-Robb Hall, Ithaca, NY 14853-5701 Although microbial degradation kinetics has traditionally been considered to be first order, there have been increasing reports about many bacteria following non-first order kinetics. In a thermal process, the uncertainties in various parameters such as the initial bacterial load can be quite large. Thus, a fundamental question in switching to a non-first order kinetic model that is expected to provide higher accuracy is whether that accuracy is retained after considering the process uncertainties. The objective of this study is to observe how uncertainty in process parameters affects the uncertainty in the final process lethality calculations, by combining both types of kinetics with a process model. Both types of kinetics are combined with a conduction heat transfer model for canning and Monte-Carlo simulations are done with 1000 repetitions. Uncertainties in first order kinetic parameters are taken from literature. Uncertainties in non-first order (Weibull) kinetic parameters have to be estimated from available values, and are assumed to be lower than the former as this is a more accurate model. In the range of literature D and z values, and b and n values, the match in the log-reduction of the two models isnt very bad. But the model based on first-order kinetics is much more sensitive to process time, and an extrapolation of results based on this model is going to be much more erroneous when compared to extrapolation based on Weibull model. For the first time, it is shown that the inclusion of variability of input parameters is as pressing an issue as changing over to a completely different model. Development of an entirely new database and procedures for non-first order kinetics is a huge task and uncertainties in the parameters should play a critical role in deciding such changes.
Session 111, Food Engineering: Modeling heat transfer and microbial inactivation
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